--- id: "digest:96" type: "Reboot Democracy weekly news digest (News That Caught Our Eye)" title: "Reboot Weekly: Controlling the Stack, Governing Sovereignty, and Training the State" url: "https://rebootdemocracy.ai/newsthatcaughtoureye/96" edition: "96" date: "2026-02-26" authors: ["Elana Banin and Dane Gambrell"] source: "Reboot Democracy (rebootdemocracy.ai)" licence: "none stated" --- # Reboot Weekly: Controlling the Stack, Governing Sovereignty, and Training the State By Elana Banin and Dane Gambrell · 26 February 2026 This week on Reboot Democracy, Beth Simone Noveck explores how governments can provide safe, affordable access to AI at scale, arguing that the real question is not buy versus build, but who controls the infrastructure. In Research Radar, she examines academic warnings about uncritical adoption and reframes the challenge as one of power and oversight. Luca Cominassi and Beth Simone Noveck then argue that sovereignty and regulation mean little without institutional capacity. Beyond Reboot, Washington, DC, ties AI training to procurement; Colorado debates data center safeguards, Stanford HAI researchers clarify what AI sovereignty requires, and new evidence shows little electoral penalty for AI-enabled deception. NPR examines bot swarms and the U.S. Department of Labor releases a national AI literacy framework. ## Events **[Effective Use of Social Media: Storytelling, Trust, and Institutional Brand](https://innovate-us.org/effective-use-of-social-media-storytelling-trust-and-institutional-brand)** – February 26, 2:00 PM ET **[Prompting Lab Office Hours: Bring your AI Questions](https://innovate-us.org/prompting-lab-office-hours)** – February 27, 2:00 PM ET **[How Not to Buy Stupid AI: A Practical Guide to Evaluating AI Products and Tools](https://innovate-us.org/how-not-to-buy-stupid-ai-a-practical-guide-to-evaluating-ai-products-and-tools)** – March 2, 12:00 PM ET **[ Navigating Crisis Communications with Confidence](https://innovate-us.org/navigating-crisis-communications-with-confidence)** – March 3, 12:00 PM ET ## AI for Governance ### [How Institutions Can Provide AI Access Safely, Affordably, and at Scale](https://rebootdemocracy.ai/blog/how-bos-nj-scale-ai-access) Reboot Democracy · Beth Simone Noveck · 2026-02-23 > As Massachusetts signs a multi-million-dollar enterprise AI contract, New Jersey and Boston offer a different path: building government-hosted AI tools inside existing cloud agreements, priced by usage rather than per seat. With costs as low as $1 per user per month in New Jersey and under $10,000 in Boston’s first year, both jurisdictions paired access with mandatory training, guardrails, and strong logging from day one. The choice is not simply buy versus build, but whether government controls its infrastructure or rents it. ### [DC​​ Becomes First Major US City to Require AI Training](https://cities-today.com/dc-becomes-first-major-us-city-to-require-ai-training/) Cities Today · Jonathan Andrews · 2026-02-19 > Washington, DC has become the first major US city to mandate responsible AI training for all government employees and contractors, embedding AI literacy into its workforce. In an interview with Cities Today, Stephen Miller, DC Chief Technology Officer, discusses this initiative. Building on Mayor’s Order 2024-028, the InnovateUS course reinforces six core AI values, including transparency, equity, privacy, and accountability. Completion is required and tied directly to tool access and procurement approval. Rather than treating training as a checkbox exercise, DC is integrating it into oversight, task force review, and real-world monitoring of enterprise AI use. ### [The Call to Create the Congressional Capacity and Technology Office (C-TECH)](https://www.popvox.org/blog/c-tech) POPVOX Foundation · Aubrey Wilson · 2026-02-24 > Arguing that Congress is falling behind both industry and the executive branch in AI adoption, Aubrey Wilson proposes the creation of a Congressional Capacity and Technology Office (C-TECH). Modeled on institutions such as CRS, CBO, and GAO, but focused on change management, training, and strategic technology support, the proposal frames AI not as a tool problem but a capacity problem. Rather than another IT shop, C-TECH would embed technical literacy and oversight into legislative operations, addressing a growing asymmetry between Congress and the systems it is charged with governing. ## Governing AI ### [Research Radar: Academics Are Sounding the Alarm on AI Adoption. Who’s Listening?](https://rebootdemocracy.ai/blog/research-radar-academics-warn-on-ai-adoption) Reboot Democracy · Beth Simone Noveck · 2026-02-24 > Reviewing a 17-author paper urging universities to resist uncritical AI adoption, Beth Simone Noveck highlights a growing concern: vendor dependency, opacity, and hype are reshaping public institutions from within. Applying existing research integrity standards, the scholars argue that many commercial AI systems fail tests of transparency and independence. But for governments, refusal isn’t realistic. The governance challenge is not whether to adopt AI but who controls it, at what layer of the stack, and on whose terms. ### [Key Takeaways from “Regulating Algorithms: What Governments Around the World Are Doing—and What Public Servants Should Know”](https://rebootdemocracy.ai/blog/regulating-algorithms-key-takeaways) Reboot Democracy · Luca Cominassi and Beth Simone Noveck · 2026-02-25 > Reducing reliance on Big Tech or investing in domestic AI systems does not automatically make AI work for the public. Drawing on examples from Spain’s ALIA project, the EU AI Act, and Italy’s new AI law, this workshop recap argues that sovereignty and regulation only go so far. What ultimately matters is institutional capacity: trained staff, procurement standards, monitoring mechanisms, and clear human accountability once systems are deployed. Democratic AI depends less on ownership alone and more on governance in practice. ## AI Infrastructure ### [Buy versus Build an LLM: A Decision Framework for Governments](https://arxiv.org/abs/2602.13033) arXiv · Jiahao Lu, Ziwei Xu, William Tjhi, Junnan Li, Antoine Bosselut, Pang Wei Koh, Mohan Kankanhalli · 2026-02-13 > As governments race to deploy large language models, this paper offers a comprehensive public-sector framework for deciding whether to buy commercial AI services, build sovereign models, or adopt hybrid approaches. Drawing on case studies from Singapore’s SEA-LION and Switzerland’s Apertus, the authors evaluate trade-offs across sovereignty, cost, security, sustainability, talent, and long-term industrial strategy. Rather than framing the decision as binary, the paper argues for pluralistic, evolving strategies that treat LLMs as public infrastructure with structured re-evaluation over time. ### [Will Colorado Give Data Centers a Warm Embrace—or a Cool Reception?](https://www.cpr.org/podcast-episode/data-center-legislation-ai-colorado-state-capitol/) CPR News / The Colorado Sun / KUNC, Feb 20, 2026 · Sam Brasch, Taylor Dolven, and Lucas Brady Woods · 2026-02-20 > As AI-driven data centers expand across Colorado, lawmakers face a defining choice: offer tax incentives to attract investment or impose stricter environmental and community safeguards. Competing bills would either subsidize new facilities or require renewable energy offsets and mitigation for rising utility costs and local impacts. Meanwhile, neighborhoods like Elyria in Denver are voicing concerns about air quality, electricity demand, and long-term community effects. The debate highlights a broader national tension over how states should govern the physical infrastructure powering AI. ## AI and International Relations ### [AI Sovereignty’s Definitional Dilemma](https://hai.stanford.edu/news/ai-sovereigntys-definitional-dilemma) Stanford HAI · Juan Pava, Caroline Meinhardt, Elena Cryst, and James Landay · 2026-02-17 > As governments race to secure “AI sovereignty,” Stanford HAI scholars argue the term remains dangerously underspecified. The concept spans incompatible meanings—from full-stack national self-sufficiency to softer notions of strategic autonomy—and shifts across layers of the AI stack, from compute and data to models and talent. The authors urge policymakers to move beyond vague calls for “control” and instead clarify why and where they seek greater agency. True sovereignty, they argue, is about managing interdependence, not pursuing costly isolation. ## AI and Elections ### [Artificial Intelligence in Election Campaigns: Perceptions, Penalties, and Implications](https://www.tandfonline.com/doi/full/10.1080/10584609.2025.2611913) Political Communication Journal · Andreas Jungherr, Adrian Rauchfleisch, and Alexander Wuttke · 2026-02-19 > Across three studies involving more than 7,600 Americans, researchers find that while the public strongly disapproves of AI-enabled deception in election campaigns, parties face no meaningful electoral penalty for using it. Instead, exposure to deceptive AI increases support for stricter regulation, including calls for an outright halt to AI development. The findings reveal a troubling misalignment: norm violations trigger regulatory backlash rather than political consequences, weakening incentives for parties to self-restrain in polarized environments. ### [‘If You Can Keep It’: A.I. And Our Democracy](https://www.npr.org/2026/02/16/if-you-can-keep-it-ai-and-our-democracy) 1A Podcast (NPR) · Jen White and Todd Zwillich · 2026-02-16 > Experts warn that AI-powered bot swarms and synthetic media are accelerating the scale and sophistication of political disinformation. With estimates suggesting up to 20% of social media accounts may be automated, and far higher on controversial topics, the episode explores how AI lowers the cost of producing persuasive lies, exploits engagement-driven algorithms, and erodes public trust. Guests highlight weak platform guardrails, limited transparency, and the absence of meaningful accountability, raising urgent questions about how democratic institutions can respond before the next election cycle. ## AI and Labor ### [U.S. Department of Labor Releases AI Literacy Framework](https://www.dol.gov/newsroom/releases/eta/eta20260213) U.S. Department of Labor · Staff · 2026-02-13 > The U.S. Department of Labor’s Employment and Training Administration has published a national AI Literacy Framework outlining five foundational content areas and seven delivery principles to guide AI skill development across workforce and education systems. Designed to support flexible adoption across industries and roles, the framework aims to accelerate AI readiness using existing Workforce Innovation and Opportunity Act funding streams and the governor’s reserve funds. Positioned within the Administration’s broader AI Action Plan and America’s Talent Strategy, the guidance emphasizes scalable workforce preparation for an AI-driven economy, with ongoing stakeholder input shaping future iterations. ## AI and Public Safety ### [Met Police Using AI Tools Supplied by Palantir to Flag Officer Misconduct](https://www.theguardian.com/uk-news/2026/feb/22/met-police-ai-tools-officer-misconduct-palantir) The Guardian · Robert Booth · 2026-02-22 > The Metropolitan Police has confirmed it is piloting AI tools from Palantir to analyze internal data—such as sickness levels, absences, and overtime patterns to identify potential misconduct among officers. While officials describe the system as pattern detection followed by human review, police unions have condemned the approach as “automated suspicion,” raising concerns about opaque profiling and employee rights. The pilot underscores a broader governance dilemma, as AI expands into public safety oversight, questions of transparency, labor protections, and vendor accountability increasingly accompany promises of cultural reform. Each item quotes its source; the excerpts are that publication's words. Follow the link for the original. * * * Original page: https://rebootdemocracy.ai/newsthatcaughtoureye/96 · Licence: none stated